{"id":"W7110949963","doi":"10.1162/imag.a.1080","title":"Revisiting the interpretation of axon diameter mapping using higher-order signal representations","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Wolfson Foundation; Center for Advanced Imaging Innovation and Research; Canada Research Chairs; National Institute of Biomedical Imaging and Bioengineering; Wellcome Trust","keywords":"Axon; Scaling; Estimator; Robustness (evolution); SIGNAL (programming language); Perpendicular; Monte Carlo method","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00166771,0.0004718782,0.0004289935,0.0008769747,0.0002611833,0.001359168,0.0008674221,0.0007661522,0.00161312],"category_scores_gemma":[0.007041839,0.0002398421,0.0004944283,0.0005221626,0.0009175867,0.001576243,0.001007169,0.001002016,0.0004050497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004866679,"about_ca_system_score_gemma":0.0005454515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001331368,"about_ca_topic_score_gemma":0.001054313,"domain_scores_codex":[0.9995263,0.0001617621,0.00003205401,0.000105898,0.0001366365,0.00003741209],"domain_scores_gemma":[0.9970451,0.00167629,0.0004139135,0.0004387257,0.0003415667,0.00008445251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003212775,0.0001490728,0.006178117,0.001039635,0.0001285885,0.001186004,0.000909054,0.2914341,0.2398579,0.1717711,0.002685723,0.2843394],"study_design_scores_gemma":[0.000007810546,0.00005463272,0.002530569,0.00003353949,0.00001924707,0.0002991772,0.00004839212,0.9534616,0.01577894,0.02603239,0.001706338,0.00002740354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05503163,0.0003851436,0.9424797,0.0002658184,0.00005931634,0.00002510724,0.00007527844,0.0004407031,0.001237355],"genre_scores_gemma":[0.7271224,0.0005832601,0.2700836,0.0001396159,0.0001038153,0.00005966731,0.0001352074,0.0002712855,0.001500993],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00166771,"threshold_uncertainty_score":0.008819818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07640376401577224,"score_gpt":0.4004362656322108,"score_spread":0.3240325016164385,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}